Thermal Infrared Image Analysis for Breast Cancer Detection

• Sedong Min,
• Jiyoung Heo,
• Youngsun Kong,
• Yunyoung Nam,
• Preap Ley,
• Bong-Keun Jung,
• Dongik Oh,
• Wonhan Shin,

Vol. 11, No. 2, February 27, 2017
10.3837/tiis.2017.02.029, Download Paper (Free):

• breast cancer
• thermal camera
• Neural Network
• relative entropy

Abstract

With the rise in popularity of photographic and video cameras, an increasing number of fields are now using thermal imaging cameras. One such application is in the diagnosis of breast cancer, as thermal imaging provides a low-cost and noninvasive method. Thermal imaging is particularly safe for pregnant women, and those with large, dense, or sensitive breasts. In addition, excessive doses of radiation, which may be used in traditional methods of breast cancer detection, can increase the risk of cancer. This paper presents one method of breast cancer detection. Breast images were taken using a thermal camera, with preliminary experiments conducted on Cambodian women. Then the experimental results were analyzed and compared using Shannon entropy and logistic regression.

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